Parameter-Based Testing and Debugging of Autonomous Driving Systems

被引:4
|
作者
Arcaini, Paolo [1 ]
Calo, Alessandro [2 ]
Ishikawa, Fuyuki [1 ]
Laurent, Thomas [3 ]
Zhang, Xiao-Yi [1 ]
Ali, Shaukat [4 ]
Hauer, Florian [2 ]
Ventresque, Anthony [3 ]
机构
[1] Natl Inst Informat, Tokyo, Japan
[2] Tech Univ Munich, Munich, Germany
[3] Univ Coll Dublin, Sch Comp Sci, Lero UCD, Dublin, Ireland
[4] Simula Res Lab, Oslo, Norway
基金
爱尔兰科学基金会;
关键词
D O I
10.1109/IVWorkshops54471.2021.9669254
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Testing of Autonomous Driving Systems (ADSs) is of paramount importance. However, ADS testing raises several challenges specific to the domain. Typical testing (coverage criteria, test generation, and oracle definition) and debugging activities performed for software programs are not directly applicable to ADSs, because of the lack of proper test oracles, and the difficulty of specifying the desired, correct ADS behavior. We tackle these challenges by extending and combining existing approaches to the domain of testing ADS. The approach is demonstrated on an industrial path planner. The path planner decides which path to follow through a cost function that uses parameters to assign a cost to the driving characteristics (e.g., lateral acceleration or speed) that must be applied in the path. These parameters implicitly describe the behavior of the ADS. We exploit this idea for defining a coverage criterion, for automatically specifying an oracle, and for debugging the path planner.
引用
收藏
页码:197 / 202
页数:6
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